Many modern mobile devices such as smart phones or wearable devices have navigation functions that depend on global navigation satellite system (GNSS) signals. In challenging GNSS environment (e.g., “urban canyons” surround by signal-blocking high-rise buildings), non-line of sight (NLOS) signals and multipath interference can cause positioning errors. Using conventional technologies, a processor can identify and reject NLOS and other distorted signals by examining signal structure. For example, the processor can identify and reject signals that have low carrier-to-noise density (C/N0) or weak signals that are inconsistent with strong signals. The conventional technologies typically can identify and reject clearly distorted signals. These technologies can fail in the presence of specular reflectors, which can reflect GNSS signals with almost no loss but can distort pseudorange and pseudorange rate measurements. In addition, if C/N0 strength is used as a metric of fidelity of a position, velocity and time (PVT) solution derived from the specularly reflected signals, a processor can be overconfident about the PVT solution. In such situations, the horizontal uncertainty of position error (HEPE) or a horizontal position uncertainty in the PVT solution can be biased incorrectly lower.